‎Data and Algorithm Ethics‎

‎Data and Algorithm Ethics‎ is an online course, offered through the German KI-Campus learning platform, created and developed by the Berlin School of Economics and Law. The technology in context here is AI (Artificial Intelligence) - and the training examines and questions the ways and logic, used by professionals in the field to determine whether an AI application is trustworthy, or could be of concern.

The course's aim is to enhance learners' ability to gathered ethically correct data and design intelligent algorithms without discrimination. Finally, participants will also find out more about cognitive bias when it comes to AI applications - and will get to test their skills through various mini-games and questionnaires within each module. 

‎The course is available in German. It is self-paced and free. 

Topics

‎Data and Algorithm Ethics zooms in on several concepts, central to AI, AI applications and their trustworthiness, including: conceptual foundations of data and different approaches to algorithm ethics, theoretical background behind current AI applications, and others. Participants will also learn the different ways in which data can be extracted, processed and sourced ethically - and how this is applied in areas such as algorithm design or AI applications. Course topics are illustrated via numerous and practical use cases (for example, learning sequences and tangible content in the context of creating ethical software games). 

Learning outcomes

Upon successful completion of this course, learners will be able to: 

• List and describe essential technical terms related to AI, data and algorithms and provide the basic theoretical context behind each one; 
• Define and explain ethics, ethical design and different approaches in the field; 
• Compare and contrast examples of data and algorithm ethics across AI applications and discuss challenges in this area; 
• Explain why trustworthiness of algorithms and the concept of harmless data is so important and how it plays a role in the design, implementation and use of AI applications; 
• Take part in discussions as part of the current AI discourse, both on national and European level.